Vivli enthusiastically congratulates Dr. Monica Bertagnolli on the White House announcement that it intends to nominate her as Director of the National Institutes of Health.
Dr. Bertagnolli has served as a long-time member on the Vivli External Advisory Committee.
“We are glad to see the intent to nominate Dr. Monica Bertagnolli to such an impactful role and we wish her all the best,” said Rebecca Li, Executive Director.
VIVLI, the Center for Global Clinical Research is seeking a Clinical Research Manager.
Vivli is a mission-focused non-profit and to help manage our continued growth, we are looking for a seasoned clinical research manager to join the operations team. The operations team supports researchers seeking to access datasets from contributors and provides support for data contributors.
Location: Remote, with a preference for East Coast or European working hours.
Responsibilities will include but not limited to:
• Manage day-to-day data request review process for specific requests.
• Work closely with Vivli end users to ensure success of the use of the platform
• Vivli platform QA
• Support the Vivli resource library.
• Lead in on-boarding new members
• Perform other duties when requested
Qualifications:
• Minimum 5 years prior experience managing data transparency processes, either at an existing repository, platform or as a data contributor
• 2-3 years experience with vendor management
• Experience in supporting researcher and/or data contributors in fulfilling data requests
• Understanding of clinical trials processes and/or clinical data management preferred
• Excellent written and oral communication skills and interpersonal skills
• Prior experience with process improvement a plus
• Computer proficiency in MS Office, Excel, PowerPoint, Sharepoint, Dropbox etc.
• Excellent organizational skills and attention to detail
• Ability to manage projects and resources
• Bachelor’s degree in the health profession, science, IT or business field
To apply, send a cover letter and CV to hr@vivli.org.
Vivli announced that its Board of Directors has promoted Rebecca Li to the position of CEO. Li previously held the position of Executive Director and has been with the Vivli since its founding when it launched as a project from the MRCT Center of the Brigham and Women’s Hospital and Harvard.
“Rebecca has overseen the extraordinary growth of Vivli from the start and we are excited that she will continue to lead Vivli through the next phase of growth as we aim to go even further in our mission to make clinical trial available for research. She has demonstrated herself to be an exceptional team leader and strategic thinker with a clear vision for how we will develop globally in the coming years,” said Dr. Michael Stebbins, Vivli’s Board Chair.
“I am privileged to lead Vivli and envision further expanding our successful platform technology into Europe and Asia as we enter our next phase of innovation and growth” said Dr. Rebecca Li.
Vivli was founded in 2018 as a non-profit organization that is currently the largest individual participant-level (IPD) data sharing platform focused on sharing clinical trial data serving the international research community.
Vivli has launched the Vivli AMR Surveillance Open Data Re-use Challenge, funded by Wellcome. The data challenge aims to stimulate and support the innovative re-use of antimicrobial resistance (AMR) surveillance data available in the AMR Register.
This Challenge provides an opportunity for multidisciplinary teams to win prizes by using high-quality industry AMR surveillance data to answer pressing research questions. The data will be shared through the AMR Register.
A series of prizes can be won by research teams from any discipline who find new insights in the data and contributes to the fight against antimicrobial resistance.
What prizes can be won?
There are five monetary awards:
• Grand Prize Award – $20,000
• 4 awards – $10,000 (each) in the categories of Innovation and Impact
Winning teams will additionally be provided with funding towards expenses for ECCMID 2024 if an abstract is accepted.
Sign up to the data challenge Slack Channel to be notified when the challenge is open and to keep updated about the latest information and details about this data challenge.
What’s involved?
Teams are invited to register and submit a short summary of the research they intend to undertake with the data (and Expression of Interest or EOI) by May 10. The EOIs will be reviewed and teams will be given access to the data for a 30-day window, during which solutions must be submitted.
These submissions will be reviewed by a panel of judges and finalists selected. Finalists will have the opportunity to pitch their idea to a panel of judges via Zoom and the prize winners will be chosen.
Winners will be invited to submit a project abstract to ECCMID 2024.
Elena Myasoedova, M.D., Ph.D., is a clinical rheumatologist with specialty interest in inflammatory arthritis. She is an associate professor of medicine and epidemiology and clinical practice, and leads research in rheumatology and specifically inflammatory arthritis at the Mayo Clinic. Dr. Myasoedova’s team submitted a research proposal to access Vivli to conduct analysis relevant to their topic, “Individualized Prediction of Treatment Response to Methotrexate in Patients with Rheumatoid Arthritis: A Machine Learning Approach”. Their completed research has been presented to the rheumatology research community at conferences and in publications including Annals of the Rheumatic Diseases. She sat down with Vivli to tell us more about accessing clinical trial data to advance her research, and the possibilities for using machine learning as a tool in clinical support for people with rheumatoid arthritis.
Please tell us a little bit more about your research – what led you to want to investigate this particular topic?
In patients with rheumatoid arthritis, methotrexate is a medicine that is used very commonly, and frequently is the first medicine and the most common medicine used in combination later on during the disease course. The challenge that we are facing in rheumatology in general is that we do not have individualized prediction of response to treatments. This means that we use a trial and error approach to treatments; we start patients on medications that are generally effective and safe, and then if a patient does not respond, we upgrade to a different medicine. Because most of the medicines that we use take weeks and months to show their effects, it’s important to understand early on if a person is likely to be a responder. That would help to save time and potentially save some unwanted side effects for the patient, and also help us to be more proactive and helpful.
For this specific study, we looked at clinical markers or clinical predictors of response to methotrexate. We found more than 1400 patients from 13 randomized trials. A total of 775 patients from 4 RCTs were included in the study, and we monitored their response across a six-month timeframe. We further evaluated whether people who did not respond to methotrexate and had some moderate to high disease activity at 12 weeks – who out of this population would respond by follow-up at 24 weeks. We also found a couple of markers for that: specifically if there was a drop in DAS28 sat rate from baseline to 12 weeks of at least 1 point, then it was predictive of then achieving remission or low disease activity at 24 weeks. Otherwise the chances were slim.
We developed this algorithm, and externally validated it using two independent trials with good results. I think that these findings advance the understanding of who are the most likely responders, and how we should discuss with patients their likelihood of response at the very start of their treatment.
Are you hoping that this is going to change the clinical approach? Has it already had an impact in clinical approaches to working with people who have arthritis?
This particular study, and similar studies would probably change the way we discuss this treatment with a patient; changing the treatment approach is a very complex task that probably has to come through the association guidelines.
Is there anything specific that you’d like to say about what working with the dataset in Vivli enabled you to do that you might not have been able to do otherwise?
It was actually a very good experience for us to work with Vivli datasets. It provided longitudinal data on patients who were users of methotrexate but not other medicines, and there were hundreds of these patients available from the trials. So it’s a fairly good dataset to work with, and it had multiple data points longitudinally. Also, at each point, there were multiple clinical points collected, so it was fairly comprehensive.
Do you have any advice that you would give to other researchers who might be interested in accessing this type of data using a platform like Vivli?
The most important advice is to put together a comprehensive proposal with a plan right off the bat, to make sure that the timeline is feasible and that the question that they want to address is feasible with the available data – just to make sure that they are not over-expecting or under-planning. I think it’s most important to ensure that the study question matches the data set.
Have you had feedback about your research and findings?
This research has been presented at several conferences, and the comments have mostly been positive, acknowledging the need for developing such algorithms.
The Leona M. and Harry B. Helmsley Charitable Trust’s Type 1 Diabetes Program has launched an initiative to support innovative and practicable solutions to help people with type 1 diabetes (T1D) exercise safely and to improve their quality of life. To help address knowledge gaps about the effect of exercise on T1D, Helmsley supported a research collaboration centered on two large observational exercise studies in people with T1D: one in adults (T1-DEXI) and one in children (T1-DEXIP). More than 500 people took part in the adult study, and another 250 in the pediatric study. Both studies were recruited and conducted fully remotely by design, enabling full monitoring and data collection which was unimpeded by COVID-19 pandemic restrictions.
The data from these studies include information about types of physical activity, heart rate, insulin use, CGM, diet, and genetics. The research collaboration collected and organized the observational data to maximize interoperability, and Helmsley has partnered with Vivli to make the data from T1-DEXI and T1-DEXIP publicly available. Sharing study data publicly will enable a range of researchers to access and explore the data from a variety of perspectives and research specialties.
In addition to facilitating public access through the Vivli platform, Helmsley has also opened a request for proposals (RFP) to support researchers, clinicians, and data scientists interested in analyzing the data and testing novel solutions in people with T1D. The RFP aims to fund projects that will improve the understanding of how exercise impacts T1D and that will provide people with T1D and their healthcare providers practical management solutions and clinical guidelines. The overarching purpose of this initiative is to move real-world data towards real-world solutions.
Concept notes for the RFP are due by April 30, 2023, and full proposals will be invited for submission later in 2023. Researchers interested in exploring the T1D dataset on Vivli in order to prepare concept notes for submission can search data publicly available through Vivli’s search portal, and submit a data request using the standard process. Complete information about the RFP, including key dates and submission criteria, is available on The Helmsley Charitable Trust site.
Deniz Dalton, Program Officer in T1D at Helmsley, said, “People with T1D face many burdensome challenges in their daily lives, including complex decisions around exercise, diet, monitoring glucose levels, and administering insulin. We are excited to make this data publicly available and to launch this RFP, to advance the understanding of how exercise affects glucose management, and ultimately to help create real-world solutions to challenges faced by people with T1D around exercise.”
For more information, please watch Dalton’s presentation on this initiative at the Vivli 2022 Annual Meeting, or contact Vivli User Support directly at support@vivli.org with any questions
Vivli held a webinar to discuss recent developments in data privacy laws and their impact on data sharing.
The webinar was held on Monday, April 24th at 3pm CEST / 2pm BST / 9am EDT.
The People’s Republic of China (PRC) enacted a comprehensive data privacy law called the Personal Information Protection Law (PIPL) in November 2021. This law adds to an already complex data privacy framework in the PRC, which also includes the Regulation of Human Genetic Resources, the Biosecurity Law of the PRC and the Data Security Law of the PRC. This webinar will focus on key implications of the PIPL and these other PRC laws for the sharing of clinical trials data generated in the PRC for further research purposes. The speakers will also make comparisons between PIPL and the European Union’s General Data Protection Regulation (“GDPR”), another global privacy law that has had a significant impact on the sharing of clinical trial data.
Learning objectives for this session include:
• Understand the basics of PIPL
• Understand how PIPL affects sharing of clinical trials data across international borders
• Understand key differences between PIPL and GDPR
Speakers:
• Rebecca Li, Vivli
• David Peloquin, Ropes & Gray
• Katherine Wang, Ropes & Gray
This webinar is intended for organizations and individuals that share data and will be particularly useful for those who focus on data privacy.
Rebecca Li will be speaking at the NIA-DUKE-Alzheimer’s Association Workshop held on March 15-16th sponsored by the National Institute on Aging.
The focus of the talk by Rebecca Li and Katherine Welsh-Bohmer (Duke University School of Medicine) is on how the Vivli platform can be used to access trials in Alzheimer’s Disease. Dr. Welsh-Bohmer will discuss the TOMMORROW trial – a large prevention study in Alzheimer’s Disease – as a specific use case.
The NIH Data Management and Sharing (DMS) policy went into effect in January 2023 to promote the sharing of scientific data.
Please watch Vivli’s recent webinar and find out more about how Vivli can help you navigate the NIH Data Management and Sharing policy. Hear from academic staff on their experiences in supporting researchers with their Data Management and Sharing Plans (DMSP).
During this webinar, we:
Speakers include:
Participants had the opportunity to ask questions. This webinar is most useful for current or prospective NIH grantees or those who support them.
Version 3.0 of the Vivli platform has been released and is available to users. The key change with the new version of the platform is that it is now possible for researchers to submit their completed clinical study through platform. This change is aimed academic researchers so they can meet funder requirements.
“To make it easier for researchers who want to share the results of their completed clinical trials to meet funder and publication requirements, it is now possible for researchers to answer a few questions and submit their studies for sharing,” said Julie Wood, Vivli Senior Director. “We think this will make it much easier for academic researchers to share their data.”
Other minor useability changes have been made and the tools and software in the research environment has been updated.